Although non-farm enterprises are ubiquitous in rural Sub-Saharan Africa, little is yet known about their productivity. In this paper we contribute to filling this gap by providing estimates of labor productivity in enterprises for Ethiopia, Malawi, Nigeria, and Uganda. Using the World Bank's...

The COVID-19 pandemic holds at least seven lessons for the relationship between data-driven decision making, the use of artificial intelligence, and development. These are that (1) in a global crisis, the shifting value of data creates policy pitfalls; (2) predictions of crises and how they play...

Sub-Saharan Africa (SSA) has the highest growth rate in net international migration in the world. The reasons for this migration are investigated in this paper. First, a survey of the literature on the profile and determinants of international migration in SSA is given. Second, panel data on 45...

We are the first to provide a comparative empirical analysis of non-farm entrepreneurship in rural Africa, using the World Bank's unique LSMSISA dataset. This dataset covers six countries over the period 2005 to 2012. We find that rural enterprises tend to be small, informal household...

Africa is not only the poorest and most rural continent, it is also the most youthful continent in terms of population. Given the large number of young job seekers that will enter the labor market over the next decade, we need a better understanding of rural non-farm entrepreneurship,...